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Investigating Power Reduction for NoC-based Spiking Neural Network Platforms using Channel Encoding

McDonnell, Neil, Carrillo, Snaider, Harkin, Jim and McDaid, Liam (2012) Investigating Power Reduction for NoC-based Spiking Neural Network Platforms using Channel Encoding. International Journal of Adaptive, Resilient, and Autonomic Systems, 4 (3). pp. 1-16. [Journal article]

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URL: http://www.igi-global.com/article/investigating-power-reduction-noc-based/74363

DOI: 10.4018/jaras.2012100101

Abstract

Recent focus has been placed on exploring the possibility to switch from parallel to serial data links between NoC routers in order to improve signal integrity in the communication channel. However, moving streams of data between the parallel path of the internal router and external serial-channel links between them consumes additional power. One challenge is encoding the data and minimise the switching activity of data in the serial links in order to reduce the additional power dissipation; while under real-time and minimal hardware constraints. Consequently, proposed is a novel low area/power decision circuit for NoC channel encoding which identifies in real-time packets for encoding and extends the existing SILENT encoders/decoders to further minimise power consumption and demonstrates the power performance savings of the decision circuitand modified (en)decoders using example test traffic with the EMBRACE NoC router, a mixed signal spiking neural network (SNNs) embedded platform.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:24880
Deposited By: Dr Jim Harkin
Deposited On:06 Feb 2013 15:16
Last Modified:06 Feb 2013 15:16

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